Application of Artificial Capital Market in Task Allocation in Multi-robot Foraging

Because of high speed, efficiency, robustness and flexibility of multi-agent systems, in recent years there has been an increasing interest in the art of these systems. Artificial market mechanisms are one of the well-known negotiation multi-agent protocols in multi-agent systems. In this paper arti...

Full description

Bibliographic Details
Main Authors: Adel Akbarimajd, Ghader Simzan
Format: Article
Language:English
Published: Atlantis Press 2014-06-01
Series:International Journal of Computational Intelligence Systems
Subjects:
Online Access:https://www.atlantis-press.com/article/25868502.pdf
id doaj-d1faa915319d44b1aedb34e1644d3d81
record_format Article
spelling doaj-d1faa915319d44b1aedb34e1644d3d812020-11-25T02:38:21ZengAtlantis PressInternational Journal of Computational Intelligence Systems 1875-68832014-06-017310.1080/18756891.2014.922814Application of Artificial Capital Market in Task Allocation in Multi-robot ForagingAdel AkbarimajdGhader SimzanBecause of high speed, efficiency, robustness and flexibility of multi-agent systems, in recent years there has been an increasing interest in the art of these systems. Artificial market mechanisms are one of the well-known negotiation multi-agent protocols in multi-agent systems. In this paper artificial capital market as a new variant of market mechanism is introduced and employed in a multi-robot foraging problem. In this artificial capital market, the robots are going to benefit via investment on some assets, defined as doing foraging task. Each investment has a cost and an outcome. Limited initial capital of the investors constrains their investments. A negotiation protocol is proposed for decision making of the agents. Qualitative analysis reveals speed of convergence, near optimal solutions and robustness of the algorithm. Numerical analysis shows advantages of the proposed method over two previously developed heuristics in terms of four performance criteria.https://www.atlantis-press.com/article/25868502.pdfTask AllocationForaging RobotsDistributed Artificial IntelligenceMulti-agent SystemsCapital Market Mechanism
collection DOAJ
language English
format Article
sources DOAJ
author Adel Akbarimajd
Ghader Simzan
spellingShingle Adel Akbarimajd
Ghader Simzan
Application of Artificial Capital Market in Task Allocation in Multi-robot Foraging
International Journal of Computational Intelligence Systems
Task Allocation
Foraging Robots
Distributed Artificial Intelligence
Multi-agent Systems
Capital Market Mechanism
author_facet Adel Akbarimajd
Ghader Simzan
author_sort Adel Akbarimajd
title Application of Artificial Capital Market in Task Allocation in Multi-robot Foraging
title_short Application of Artificial Capital Market in Task Allocation in Multi-robot Foraging
title_full Application of Artificial Capital Market in Task Allocation in Multi-robot Foraging
title_fullStr Application of Artificial Capital Market in Task Allocation in Multi-robot Foraging
title_full_unstemmed Application of Artificial Capital Market in Task Allocation in Multi-robot Foraging
title_sort application of artificial capital market in task allocation in multi-robot foraging
publisher Atlantis Press
series International Journal of Computational Intelligence Systems
issn 1875-6883
publishDate 2014-06-01
description Because of high speed, efficiency, robustness and flexibility of multi-agent systems, in recent years there has been an increasing interest in the art of these systems. Artificial market mechanisms are one of the well-known negotiation multi-agent protocols in multi-agent systems. In this paper artificial capital market as a new variant of market mechanism is introduced and employed in a multi-robot foraging problem. In this artificial capital market, the robots are going to benefit via investment on some assets, defined as doing foraging task. Each investment has a cost and an outcome. Limited initial capital of the investors constrains their investments. A negotiation protocol is proposed for decision making of the agents. Qualitative analysis reveals speed of convergence, near optimal solutions and robustness of the algorithm. Numerical analysis shows advantages of the proposed method over two previously developed heuristics in terms of four performance criteria.
topic Task Allocation
Foraging Robots
Distributed Artificial Intelligence
Multi-agent Systems
Capital Market Mechanism
url https://www.atlantis-press.com/article/25868502.pdf
work_keys_str_mv AT adelakbarimajd applicationofartificialcapitalmarketintaskallocationinmultirobotforaging
AT ghadersimzan applicationofartificialcapitalmarketintaskallocationinmultirobotforaging
_version_ 1724791424191299584